Overview

Dataset statistics

Number of variables42
Number of observations221
Missing cells3283
Missing cells (%)35.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory354.2 KiB
Average record size in memory1.6 KiB

Variable types

CAT21
NUM11
UNSUPPORTED6
BOOL4

Warnings

Model Name has a high cardinality: 109 distinct values High cardinality
Model Number has a high cardinality: 186 distinct values High cardinality
Additional Model Information has a high cardinality: 73 distinct values High cardinality
Date Available on Market has a high cardinality: 62 distinct values High cardinality
Date Certified has a high cardinality: 113 distinct values High cardinality
ENERGY STAR Lamp ESUID is highly correlated with ENERGY STAR Unique IDHigh correlation
ENERGY STAR Unique ID is highly correlated with ENERGY STAR Lamp ESUIDHigh correlation
Total Lighting Input Power (Watts) is highly correlated with Total Light Output (lumens)High correlation
Total Light Output (lumens) is highly correlated with Total Lighting Input Power (Watts)High correlation
Brand Name is highly correlated with ENERGY STAR Partner and 2 other fieldsHigh correlation
ENERGY STAR Partner is highly correlated with Brand Name and 3 other fieldsHigh correlation
Ceiling Fan Features is highly correlated with ENERGY STAR Partner and 3 other fieldsHigh correlation
ENERGY STAR Lamp Partner is highly correlated with ENERGY STAR Partner and 1 other fieldsHigh correlation
Lamp Model Number is highly correlated with ENERGY STAR Partner and 3 other fieldsHigh correlation
Light Color Appearance (CCT) is highly correlated with Ceiling Fan FeaturesHigh correlation
Light Source Rated Life (Hours) is highly correlated with Ceiling Fan FeaturesHigh correlation
Date Available on Market is highly correlated with Lamp Model NumberHigh correlation
Additional Model Information has 129 (58.4%) missing values Missing
Fan Power Consumption-Low Speed (W) has 28 (12.7%) missing values Missing
Ceiling Fan Features has 5 (2.3%) missing values Missing
ENERGY STAR Lamp ESUID has 203 (91.9%) missing values Missing
Alternate ENERGY STAR Lamps ESUIDs has 221 (100.0%) missing values Missing
ENERGY STAR Lamp Partner has 80 (36.2%) missing values Missing
Lamp Model Number has 203 (91.9%) missing values Missing
Light Source Technology has 203 (91.9%) missing values Missing
Total Light Output (lumens) has 80 (36.2%) missing values Missing
Total Lighting Input Power (Watts) has 80 (36.2%) missing values Missing
Lighting Efficiency – Measured outside the Fixture (lm/W) has 221 (100.0%) missing values Missing
Lighting Efficiency – Measured at the Source (lm/W) has 221 (100.0%) missing values Missing
Power Factor of Light Kit has 80 (36.2%) missing values Missing
Light Color Appearance (CCT) has 80 (36.2%) missing values Missing
Light Color Quality (CRI) has 80 (36.2%) missing values Missing
Light Source Rated Life (Hours) has 80 (36.2%) missing values Missing
Light Sources Per Light Kit has 203 (91.9%) missing values Missing
Light Source Connection/Base Type has 203 (91.9%) missing values Missing
Special Lighting Features (Dimming, Motion Sensing, etc.) has 221 (100.0%) missing values Missing
Ceiling Fan Light Kit Warranty (yrs) has 221 (100.0%) missing values Missing
Connects Using has 220 (99.5%) missing values Missing
Notes has 221 (100.0%) missing values Missing
Model Number is uniformly distributed Uniform
ENERGY STAR Unique ID has unique values Unique
CB Model Identifier has unique values Unique
Alternate ENERGY STAR Lamps ESUIDs is an unsupported type, check if it needs cleaning or further analysis Unsupported
Lighting Efficiency – Measured outside the Fixture (lm/W) is an unsupported type, check if it needs cleaning or further analysis Unsupported
Lighting Efficiency – Measured at the Source (lm/W) is an unsupported type, check if it needs cleaning or further analysis Unsupported
Special Lighting Features (Dimming, Motion Sensing, etc.) is an unsupported type, check if it needs cleaning or further analysis Unsupported
Ceiling Fan Light Kit Warranty (yrs) is an unsupported type, check if it needs cleaning or further analysis Unsupported
Notes is an unsupported type, check if it needs cleaning or further analysis Unsupported
Fan Power Consumption-Standby (W) has 22 (10.0%) zeros Zeros

Reproduction

Analysis started2020-12-13 00:59:50.974888
Analysis finished2020-12-13 01:00:03.024758
Duration12.05 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

ENERGY STAR Unique ID
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct221
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2341270.873
Minimum2313943
Maximum2361262
Zeros0
Zeros (%)0.0%
Memory size1.9 KiB
2020-12-12T20:00:03.101825image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum2313943
5-th percentile2320995
Q12332410
median2338483
Q32353844
95-th percentile2359772
Maximum2361262
Range47319
Interquartile range (IQR)21434

Descriptive statistics

Standard deviation12908.36015
Coefficient of variation (CV)0.005513398853
Kurtosis-1.219538499
Mean2341270.873
Median Absolute Deviation (MAD)12529
Skewness-0.09795495312
Sum517420863
Variance166625761.7
MonotocityNot monotonic
2020-12-12T20:00:03.191401image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
232601410.5%
 
235946410.5%
 
232099410.5%
 
232222110.5%
 
232159210.5%
 
232144210.5%
 
233848510.5%
 
235384410.5%
 
233848310.5%
 
233848210.5%
 
233028810.5%
 
235216110.5%
 
235844110.5%
 
232464710.5%
 
235386010.5%
 
235384710.5%
 
233210810.5%
 
234985210.5%
 
234231210.5%
 
235689210.5%
 
235527210.5%
 
235841310.5%
 
235827310.5%
 
234960410.5%
 
233462610.5%
 
Other values (196)19688.7%
 
ValueCountFrequency (%) 
231394310.5%
 
231856510.5%
 
231856910.5%
 
231857010.5%
 
232098810.5%
 
232098910.5%
 
232099010.5%
 
232099110.5%
 
232099210.5%
 
232099310.5%
 
ValueCountFrequency (%) 
236126210.5%
 
236126110.5%
 
236001110.5%
 
236001010.5%
 
236000910.5%
 
236000810.5%
 
235980610.5%
 
235980510.5%
 
235977510.5%
 
235977410.5%
 

ENERGY STAR Partner
Categorical

HIGH CORRELATION

Distinct17
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Fanimation Inc.
44 
Generation Brands
33 
WAC Lighting
31 
Big Ass Fans
25 
Aeratron Pty Ltd
18 
Other values (12)
70 
ValueCountFrequency (%) 
Fanimation Inc.4419.9%
 
Generation Brands3314.9%
 
WAC Lighting3114.0%
 
Big Ass Fans2511.3%
 
Aeratron Pty Ltd188.1%
 
The Home Depot146.3%
 
Royal Pacific Ltd.135.9%
 
Kichler Lighting94.1%
 
Minka Group62.7%
 
Litex Industries, Inc./ Ellington Fans62.7%
 
Sunway Fan Company, Inc.62.7%
 
American De Rosa Lamparts, LLC (dba Luminance Brands)62.7%
 
Ellen Lighting, Inc52.3%
 
Hunter Fan Company20.9%
 
Westinghouse Lighting Corporation10.5%
 
Progress Lighting10.5%
 
Palm Coast Imports10.5%
 
2020-12-12T20:00:03.276475image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)1.4%
2020-12-12T20:00:03.346035image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length53
Median length15
Mean length16.78733032
Min length11

Overview of Unicode Properties

Unique unicode characters45
Unique unicode categories6 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n42311.4%
 
3669.9%
 
i3138.4%
 
a3028.1%
 
t2356.3%
 
e1754.7%
 
o1694.6%
 
s1504.0%
 
r1484.0%
 
g1273.4%
 
c1082.9%
 
L1082.9%
 
m862.3%
 
F832.2%
 
d822.2%
 
A802.2%
 
h711.9%
 
.691.9%
 
I681.8%
 
B641.7%
 
C471.3%
 
y451.2%
 
l451.2%
 
G391.1%
 
p361.0%
 
Other values (20)2717.3%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter257969.5%
 
Uppercase Letter65517.7%
 
Space Separator3669.9%
 
Other Punctuation982.6%
 
Open Punctuation60.2%
 
Close Punctuation60.2%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
L10816.5%
 
F8312.7%
 
A8012.2%
 
I6810.4%
 
B649.8%
 
C477.2%
 
G396.0%
 
P335.0%
 
W324.9%
 
D203.1%
 
R192.9%
 
H162.4%
 
T142.1%
 
E111.7%
 
K91.4%
 
M60.9%
 
S60.9%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n42316.4%
 
i31312.1%
 
a30211.7%
 
t2359.1%
 
e1756.8%
 
o1696.6%
 
s1505.8%
 
r1485.7%
 
g1274.9%
 
c1084.2%
 
m863.3%
 
d823.2%
 
h712.8%
 
y451.7%
 
l451.7%
 
p361.4%
 
u271.0%
 
f130.5%
 
b60.2%
 
x60.2%
 
k60.2%
 
w60.2%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
366100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.6970.4%
 
,2323.5%
 
/66.1%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(6100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)6100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin323487.2%
 
Common47612.8%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n42313.1%
 
i3139.7%
 
a3029.3%
 
t2357.3%
 
e1755.4%
 
o1695.2%
 
s1504.6%
 
r1484.6%
 
g1273.9%
 
c1083.3%
 
L1083.3%
 
m862.7%
 
F832.6%
 
d822.5%
 
A802.5%
 
h712.2%
 
I682.1%
 
B642.0%
 
C471.5%
 
y451.4%
 
l451.4%
 
G391.2%
 
p361.1%
 
P331.0%
 
W321.0%
 
Other values (14)1655.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
36676.9%
 
.6914.5%
 
,234.8%
 
(61.3%
 
)61.3%
 
/61.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII3710100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n42311.4%
 
3669.9%
 
i3138.4%
 
a3028.1%
 
t2356.3%
 
e1754.7%
 
o1694.6%
 
s1504.0%
 
r1484.0%
 
g1273.4%
 
c1082.9%
 
L1082.9%
 
m862.3%
 
F832.2%
 
d822.2%
 
A802.2%
 
h711.9%
 
.691.9%
 
I681.8%
 
B641.7%
 
C471.3%
 
y451.2%
 
l451.2%
 
G391.1%
 
p361.0%
 
Other values (20)2717.3%
 

Brand Name
Categorical

HIGH CORRELATION

Distinct29
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Fanimation
33 
Monte Carlo
32 
AERATRON
18 
MODERN FORMS
17 
Haiku
14 
Other values (24)
107 
ValueCountFrequency (%) 
Fanimation3314.9%
 
Monte Carlo3214.5%
 
AERATRON188.1%
 
MODERN FORMS177.7%
 
Haiku146.3%
 
RP Lighting & Fans135.9%
 
WAC Lighting135.9%
 
i6104.5%
 
Hampton Bay104.5%
 
Fanimation Studio Collection94.1%
 
Kichler Lighting73.2%
 
Minka Aire62.7%
 
Craftmade62.7%
 
Emerson52.3%
 
Biltmore Lighting52.3%
 
Home Decorators Collection41.8%
 
Rejuvenation20.9%
 
VIVIO20.9%
 
Arkwright Motor20.9%
 
HOMENHANCEMENTS20.9%
 
Hunter20.9%
 
SUNWAY20.9%
 
Harbor Breeze10.5%
 
WAC Lighting Co.10.5%
 
Progress Lighting10.5%
 
Other values (4)41.8%
 
2020-12-12T20:00:03.427105image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique7 ?
Unique (%)3.2%
2020-12-12T20:00:03.505172image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length28
Median length11
Mean length11.45701357
Min length2

Overview of Unicode Properties

Unique unicode characters49
Unique unicode categories5 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
i2399.4%
 
n2138.4%
 
a1917.5%
 
o1867.3%
 
t1726.8%
 
1656.5%
 
e973.8%
 
R853.4%
 
r843.3%
 
g843.3%
 
M793.1%
 
F732.9%
 
m722.8%
 
l722.8%
 
C712.8%
 
A622.4%
 
O562.2%
 
h502.0%
 
E461.8%
 
N431.7%
 
L421.7%
 
H351.4%
 
S301.2%
 
u281.1%
 
s271.1%
 
Other values (24)2309.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter161263.7%
 
Uppercase Letter73128.9%
 
Space Separator1656.5%
 
Other Punctuation140.6%
 
Decimal Number100.4%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
R8511.6%
 
M7910.8%
 
F7310.0%
 
C719.7%
 
A628.5%
 
O567.7%
 
E466.3%
 
N435.9%
 
L425.7%
 
H354.8%
 
S304.1%
 
D223.0%
 
T212.9%
 
W172.3%
 
B162.2%
 
P141.9%
 
K71.0%
 
V40.5%
 
I40.5%
 
U20.3%
 
Y20.3%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
i23914.8%
 
n21313.2%
 
a19111.8%
 
o18611.5%
 
t17210.7%
 
e976.0%
 
r845.2%
 
g845.2%
 
m724.5%
 
l724.5%
 
h503.1%
 
u281.7%
 
s271.7%
 
c251.6%
 
k221.4%
 
d161.0%
 
p100.6%
 
y100.6%
 
f60.4%
 
j20.1%
 
v20.1%
 
w20.1%
 
b10.1%
 
z10.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
165100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
610100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
&1392.9%
 
.17.1%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin234392.5%
 
Common1897.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
i23910.2%
 
n2139.1%
 
a1918.2%
 
o1867.9%
 
t1727.3%
 
e974.1%
 
R853.6%
 
r843.6%
 
g843.6%
 
M793.4%
 
F733.1%
 
m723.1%
 
l723.1%
 
C713.0%
 
A622.6%
 
O562.4%
 
h502.1%
 
E462.0%
 
N431.8%
 
L421.8%
 
H351.5%
 
S301.3%
 
u281.2%
 
s271.2%
 
c251.1%
 
Other values (20)1817.7%
 

Most frequent Common characters

ValueCountFrequency (%) 
16587.3%
 
&136.9%
 
6105.3%
 
.10.5%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII2532100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
i2399.4%
 
n2138.4%
 
a1917.5%
 
o1867.3%
 
t1726.8%
 
1656.5%
 
e973.8%
 
R853.4%
 
r843.3%
 
g843.3%
 
M793.1%
 
F732.9%
 
m722.8%
 
l722.8%
 
C712.8%
 
A622.4%
 
O562.2%
 
h502.0%
 
E461.8%
 
N431.7%
 
L421.7%
 
H351.4%
 
S301.2%
 
u281.1%
 
s271.1%
 
Other values (24)2309.1%
 

Model Name
Categorical

HIGH CARDINALITY

Distinct109
Distinct (%)49.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Ceiling Fan
33 
Haiku
 
14
i6
 
10
TRIAIRE CUSTOM
 
8
WRAP CUSTOM
 
8
Other values (104)
148 
ValueCountFrequency (%) 
Ceiling Fan3314.9%
 
Haiku146.3%
 
i6104.5%
 
TRIAIRE CUSTOM83.6%
 
WRAP CUSTOM83.6%
 
60" Ceiling Fan41.8%
 
STELLAR CUSTOM41.8%
 
Odyssey 5241.8%
 
Desert Sun41.8%
 
54" Ceiling Fan41.8%
 
ODYN CUSTOM31.4%
 
Maverick LED31.4%
 
Wynd31.4%
 
Europa III20.9%
 
LEVON CUSTOM20.9%
 
Supreme Air 56" Plus20.9%
 
Arctic II20.9%
 
Mirage III20.9%
 
ORB20.9%
 
Kingston20.9%
 
54”Kensgrove ceiling fan20.9%
 
Vox Flush20.9%
 
52" DC Builder ES20.9%
 
Roboto20.9%
 
Mocha20.9%
 
Other values (84)9543.0%
 
2020-12-12T20:00:03.594749image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique73 ?
Unique (%)33.0%
2020-12-12T20:00:03.679322image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length24
Median length10
Mean length9.701357466
Min length2

Overview of Unicode Properties

Unique unicode characters63
Unique unicode categories9 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
1868.7%
 
i1677.8%
 
n1346.2%
 
e1215.6%
 
a1034.8%
 
C934.3%
 
l773.6%
 
r632.9%
 
g612.8%
 
F542.5%
 
I522.4%
 
O502.3%
 
S502.3%
 
u482.2%
 
T472.2%
 
M462.1%
 
o452.1%
 
5442.1%
 
R432.0%
 
6391.8%
 
s381.8%
 
A381.8%
 
"371.7%
 
2361.7%
 
E311.4%
 
Other values (38)44120.6%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter104048.5%
 
Uppercase Letter68732.0%
 
Space Separator1868.7%
 
Decimal Number1798.3%
 
Other Punctuation371.7%
 
Dash Punctuation70.3%
 
Final Punctuation40.2%
 
Open Punctuation20.1%
 
Close Punctuation20.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
C9313.5%
 
F547.9%
 
I527.6%
 
O507.3%
 
S507.3%
 
T476.8%
 
M466.7%
 
R436.3%
 
A385.5%
 
E314.5%
 
L284.1%
 
U284.1%
 
D263.8%
 
P172.5%
 
H172.5%
 
W152.2%
 
N111.6%
 
V91.3%
 
B91.3%
 
K81.2%
 
Y60.9%
 
G60.9%
 
Z30.4%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
i16716.1%
 
n13412.9%
 
e12111.6%
 
a1039.9%
 
l777.4%
 
r636.1%
 
g615.9%
 
u484.6%
 
o454.3%
 
s383.7%
 
t292.8%
 
k252.4%
 
v181.7%
 
d171.6%
 
c171.6%
 
m161.5%
 
y161.5%
 
p141.3%
 
h111.1%
 
x60.6%
 
w50.5%
 
f30.3%
 
b30.3%
 
z20.2%
 
q10.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
186100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
54424.6%
 
63921.8%
 
23620.1%
 
4179.5%
 
0158.4%
 
8137.3%
 
795.0%
 
152.8%
 
910.6%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
"37100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(2100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)2100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-7100.0%
 

Most frequent Final Punctuation characters

ValueCountFrequency (%) 
4100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin172780.6%
 
Common41719.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
i1679.7%
 
n1347.8%
 
e1217.0%
 
a1036.0%
 
C935.4%
 
l774.5%
 
r633.6%
 
g613.5%
 
F543.1%
 
I523.0%
 
O502.9%
 
S502.9%
 
u482.8%
 
T472.7%
 
M462.7%
 
o452.6%
 
R432.5%
 
s382.2%
 
A382.2%
 
E311.8%
 
t291.7%
 
L281.6%
 
U281.6%
 
D261.5%
 
k251.4%
 
Other values (23)23013.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
18644.6%
 
54410.6%
 
6399.4%
 
"378.9%
 
2368.6%
 
4174.1%
 
0153.6%
 
8133.1%
 
792.2%
 
-71.7%
 
151.2%
 
41.0%
 
(20.5%
 
)20.5%
 
910.2%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII214099.8%
 
Punctuation40.2%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
1868.7%
 
i1677.8%
 
n1346.3%
 
e1215.7%
 
a1034.8%
 
C934.3%
 
l773.6%
 
r632.9%
 
g612.9%
 
F542.5%
 
I522.4%
 
O502.3%
 
S502.3%
 
u482.2%
 
T472.2%
 
M462.1%
 
o452.1%
 
5442.1%
 
R432.0%
 
6391.8%
 
s381.8%
 
A381.8%
 
"371.7%
 
2361.7%
 
E311.4%
 
Other values (37)43720.4%
 

Most frequent Punctuation characters

ValueCountFrequency (%) 
4100.0%
 

Model Number
Categorical

HIGH CARDINALITY
UNIFORM

Distinct186
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
MAD8514*
 
5
MAD8530*
 
5
F-005L
 
4
MAD8531*
 
3
B552ES
 
3
Other values (181)
201 
ValueCountFrequency (%) 
MAD8514*52.3%
 
MAD8530*52.3%
 
F-005L41.8%
 
MAD8531*31.4%
 
B552ES31.4%
 
MAD8515*31.4%
 
SUN505ESLED31.4%
 
YG493A-***20.9%
 
8KGR7220.9%
 
MAD7997*20.9%
 
MK-I61-06190620.9%
 
LP8377*20.9%
 
C57520.9%
 
CF83520.9%
 
105520.9%
 
MAD7912*20.9%
 
1055-WC20.9%
 
LP8359*20.9%
 
3OVR6020.9%
 
5HVDC52***D20.9%
 
AL583KCL/CP141050XX/ 300146XXX20.9%
 
AM588-***20.9%
 
MK-I61-06180620.9%
 
3ARR68XXX10.5%
 
OPT52***510.5%
 
Other values (161)16172.9%
 
2020-12-12T20:00:03.775404image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique163 ?
Unique (%)73.8%
2020-12-12T20:00:03.866983image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length109
Median length9
Mean length12.73755656
Min length4

Overview of Unicode Properties

Unique unicode characters70
Unique unicode categories10 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
-2057.3%
 
02037.2%
 
*1916.8%
 
51535.4%
 
11455.2%
 
1334.7%
 
21003.6%
 
A993.5%
 
8943.3%
 
3943.3%
 
D843.0%
 
6782.8%
 
L712.5%
 
M602.1%
 
F592.1%
 
a592.1%
 
4582.1%
 
R501.8%
 
C491.7%
 
7471.7%
 
9451.6%
 
E431.5%
 
W371.3%
 
r341.2%
 
n341.2%
 
Other values (45)59021.0%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number101736.1%
 
Uppercase Letter78127.7%
 
Lowercase Letter39213.9%
 
Other Punctuation2237.9%
 
Dash Punctuation2057.3%
 
Space Separator1334.7%
 
Math Symbol341.2%
 
Open Punctuation110.4%
 
Close Punctuation110.4%
 
Connector Punctuation80.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
A9912.7%
 
D8410.8%
 
L719.1%
 
M607.7%
 
F597.6%
 
R506.4%
 
C496.3%
 
E435.5%
 
W374.7%
 
S344.4%
 
X324.1%
 
P253.2%
 
B243.1%
 
V182.3%
 
I182.3%
 
K172.2%
 
T111.4%
 
H101.3%
 
N91.2%
 
Z81.0%
 
G81.0%
 
O60.8%
 
U50.6%
 
Y30.4%
 
Q10.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
020320.0%
 
515315.0%
 
114514.3%
 
21009.8%
 
8949.2%
 
3949.2%
 
6787.7%
 
4585.7%
 
7474.6%
 
9454.4%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
*19185.7%
 
,156.7%
 
"104.5%
 
/73.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
133100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(11100.0%
 

Most frequent Math Symbol characters

ValueCountFrequency (%) 
~1441.2%
 
+1338.2%
 
=720.6%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
a5915.1%
 
r348.7%
 
n348.7%
 
e338.4%
 
b297.4%
 
l225.6%
 
o215.4%
 
i215.4%
 
m153.8%
 
t153.8%
 
h143.6%
 
g143.6%
 
s133.3%
 
k123.1%
 
u123.1%
 
v102.6%
 
c102.6%
 
y92.3%
 
d61.5%
 
p41.0%
 
f30.8%
 
x10.3%
 
w10.3%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)11100.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_8100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-205100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common164258.3%
 
Latin117341.7%
 

Most frequent Latin characters

ValueCountFrequency (%) 
A998.4%
 
D847.2%
 
L716.1%
 
M605.1%
 
F595.0%
 
a595.0%
 
R504.3%
 
C494.2%
 
E433.7%
 
W373.2%
 
r342.9%
 
n342.9%
 
S342.9%
 
e332.8%
 
X322.7%
 
b292.5%
 
P252.1%
 
B242.0%
 
l221.9%
 
o211.8%
 
i211.8%
 
V181.5%
 
I181.5%
 
K171.4%
 
m151.3%
 
Other values (23)18515.8%
 

Most frequent Common characters

ValueCountFrequency (%) 
-20512.5%
 
020312.4%
 
*19111.6%
 
51539.3%
 
11458.8%
 
1338.1%
 
21006.1%
 
8945.7%
 
3945.7%
 
6784.8%
 
4583.5%
 
7472.9%
 
9452.7%
 
,150.9%
 
~140.9%
 
+130.8%
 
(110.7%
 
)110.7%
 
"100.6%
 
_80.5%
 
=70.4%
 
/70.4%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII2815100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
-2057.3%
 
02037.2%
 
*1916.8%
 
51535.4%
 
11455.2%
 
1334.7%
 
21003.6%
 
A993.5%
 
8943.3%
 
3943.3%
 
D843.0%
 
6782.8%
 
L712.5%
 
M602.1%
 
F592.1%
 
a592.1%
 
4582.1%
 
R501.8%
 
C491.7%
 
7471.7%
 
9451.6%
 
E431.5%
 
W371.3%
 
r341.2%
 
n341.2%
 
Other values (45)59021.0%
 

Additional Model Information
Categorical

HIGH CARDINALITY
MISSING

Distinct73
Distinct (%)79.3%
Missing129
Missing (%)58.4%
Memory size1.9 KiB
,,SenseME
,,F-005L-** ("**'' can be any length of characters or blank)
 
4
Ceiling Fan,SUN505ESLED*,
 
3
Ceiling Fan,B552ES*,
 
3
PROP,588961,
 
2
Other values (68)
72 
ValueCountFrequency (%) 
,,SenseME83.6%
 
,,F-005L-** ("**'' can be any length of characters or blank)41.8%
 
Ceiling Fan,SUN505ESLED*,31.4%
 
Ceiling Fan,B552ES*,31.4%
 
PROP,588961,20.9%
 
COVERT,588962,20.9%
 
54”Kensgrove ceiling fan,YG493A-BN,; 54”Kensgrove ceiling fan,YG493A-EB,; 54”Kensgrove ceiling fan,YG493A-WH,20.9%
 
BLITZ,883778,20.9%
 
54" Ceiling Fan,AM588-BN,; 54" Ceiling Fan,AM588-EB,20.9%
 
ORB,F-004-* ("*" can be any length of characters or blank),10.5%
 
,,FR-W2001-52L-** ("**" can be any length of characters or blank)10.5%
 
,,581598, 79539210.5%
 
SLINGER v2,LP8147*,10.5%
 
,,F-001L-* ("*" can be any length of characters or blank)10.5%
 
54" Midway ECO,CF955-3,10.5%
 
,S3127-A2-BCO-04-02-C-01 S3127-A2-BCS-04-02-C-01 S3127-A2-BCW-04-02-C-01 S3127-A2-BW-04-02-C-01 S3127-A2-BWO-04-02-C-01 S3127-A2-BWS-04-02-C-01 S3127-A2-BWW-04-02-C-01 S3127-A2-B*-04-02-C-01,SenseME10.5%
 
54" Ceiling Fan,AM581-BN_standard mounting,; 54" Ceiling Fan,AM581-EB_standard mounting,10.5%
 
52 Slim,FR-W2003-52L,10.5%
 
52 Clean,F-003,10.5%
 
60" Ceiling Fan,AM581A-BN_standard mounting,; 60" Ceiling Fan,AM581A-EB_standard mounting,10.5%
 
,,FR-W1801-52L-* ("*" can be any length of characters or blank)10.5%
 
Aspen,56SG7-D,10.5%
 
60" Ceiling Fan,AM581A-BN_hugger mounting,; 60" Ceiling Fan,AM581A-EB_hugger mounting,10.5%
 
,3AKR56*****,; ,3AKR56*****-*#,; ,3AKR56****,; ,3AKR56****-*#,; ,3AKR56***,; ,3AKR56***-*#,; ,3AKR56**,; ,3AKR56**-*#,; ,3AKR56BK,; ,3AKR56BKD,; ,3AKR56CH,; ,3AKR56CHD,; ,3AKR56RZW,; ,3AKR56RZWD,; ,56SGY,; ,56SGY-L,; ,56SGY-L-D,; ,AKOVA,10.5%
 
Supreme Air 56" Plus,LT10-14B-CF-Damp,10.5%
 
Other values (48)4821.7%
 
(Missing)12958.4%
 
2020-12-12T20:00:03.959563image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique64 ?
Unique (%)69.6%
2020-12-12T20:00:04.057647image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length295
Median length3
Mean length37.12217195
Min length3

Overview of Unicode Properties

Unique unicode characters72
Unique unicode categories12 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
-99712.2%
 
06427.8%
 
n4745.8%
 
14064.9%
 
3684.5%
 
23664.5%
 
,3254.0%
 
a3003.7%
 
*2883.5%
 
52272.8%
 
32232.7%
 
42232.7%
 
S2162.6%
 
A2012.5%
 
C1712.1%
 
e1712.1%
 
61511.8%
 
F1341.6%
 
B1291.6%
 
1251.5%
 
r1031.3%
 
8971.2%
 
i951.2%
 
l941.1%
 
W921.1%
 
Other values (47)158619.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number247030.1%
 
Lowercase Letter186622.7%
 
Uppercase Letter155218.9%
 
Dash Punctuation99712.2%
 
Other Punctuation7629.3%
 
Space Separator3684.5%
 
Control1251.5%
 
Open Punctuation200.2%
 
Close Punctuation200.2%
 
Connector Punctuation120.1%
 
Math Symbol60.1%
 
Final Punctuation60.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n47425.4%
 
a30016.1%
 
e1719.2%
 
r1035.5%
 
i955.1%
 
l945.0%
 
g854.6%
 
t733.9%
 
o693.7%
 
c693.7%
 
s663.5%
 
h502.7%
 
b422.3%
 
u402.1%
 
k281.5%
 
f261.4%
 
y231.2%
 
m231.2%
 
d140.8%
 
p100.5%
 
v80.4%
 
x20.1%
 
w10.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
S21613.9%
 
A20113.0%
 
C17111.0%
 
F1348.6%
 
B1298.3%
 
W925.9%
 
R664.3%
 
M664.3%
 
X644.1%
 
I533.4%
 
L523.4%
 
E493.2%
 
K473.0%
 
D463.0%
 
O322.1%
 
V291.9%
 
P251.6%
 
G201.3%
 
N140.9%
 
T130.8%
 
Y130.8%
 
H90.6%
 
Z80.5%
 
U30.2%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
,32542.7%
 
*28837.8%
 
;688.9%
 
"628.1%
 
#111.4%
 
'81.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
064226.0%
 
140616.4%
 
236614.8%
 
52279.2%
 
32239.0%
 
42239.0%
 
61516.1%
 
8973.9%
 
7913.7%
 
9441.8%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
368100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-997100.0%
 

Most frequent Control characters

ValueCountFrequency (%) 
125100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(20100.0%
 

Most frequent Math Symbol characters

ValueCountFrequency (%) 
~466.7%
 
=233.3%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)20100.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_12100.0%
 

Most frequent Final Punctuation characters

ValueCountFrequency (%) 
6100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common478658.3%
 
Latin341841.7%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n47413.9%
 
a3008.8%
 
S2166.3%
 
A2015.9%
 
C1715.0%
 
e1715.0%
 
F1343.9%
 
B1293.8%
 
r1033.0%
 
i952.8%
 
l942.8%
 
W922.7%
 
g852.5%
 
t732.1%
 
o692.0%
 
c692.0%
 
R661.9%
 
s661.9%
 
M661.9%
 
X641.9%
 
I531.6%
 
L521.5%
 
h501.5%
 
E491.4%
 
K471.4%
 
Other values (22)42912.6%
 

Most frequent Common characters

ValueCountFrequency (%) 
-99720.8%
 
064213.4%
 
14068.5%
 
3687.7%
 
23667.6%
 
,3256.8%
 
*2886.0%
 
52274.7%
 
32234.7%
 
42234.7%
 
61513.2%
 
1252.6%
 
8972.0%
 
7911.9%
 
;681.4%
 
"621.3%
 
9440.9%
 
(200.4%
 
)200.4%
 
_120.3%
 
#110.2%
 
'80.2%
 
60.1%
 
~40.1%
 
=2< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII819899.9%
 
Punctuation60.1%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
-99712.2%
 
06427.8%
 
n4745.8%
 
14065.0%
 
3684.5%
 
23664.5%
 
,3254.0%
 
a3003.7%
 
*2883.5%
 
52272.8%
 
32232.7%
 
42232.7%
 
S2162.6%
 
A2012.5%
 
C1712.1%
 
e1712.1%
 
61511.8%
 
F1341.6%
 
B1291.6%
 
1251.5%
 
r1031.3%
 
8971.2%
 
i951.2%
 
l941.1%
 
W921.1%
 
Other values (46)158019.3%
 

Most frequent Punctuation characters

ValueCountFrequency (%) 
6100.0%
 

Indoor/Outdoor
Categorical

Distinct4
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Indoor Ceiling Fan
170 
Outdoor Ceiling Fan
42 
Outdoor Ceiling Fan,Indoor Ceiling Fan
 
6
Indoor Ceiling Fan,Outdoor Ceiling Fan
 
3
ValueCountFrequency (%) 
Indoor Ceiling Fan17076.9%
 
Outdoor Ceiling Fan4219.0%
 
Outdoor Ceiling Fan,Indoor Ceiling Fan62.7%
 
Indoor Ceiling Fan,Outdoor Ceiling Fan31.4%
 
2020-12-12T20:00:04.144722image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:00:04.193764image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:00:04.260322image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length38
Median length18
Mean length19.00452489
Min length18

Overview of Unicode Properties

Unique unicode characters17
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n63915.2%
 
o46011.0%
 
46011.0%
 
i46011.0%
 
d2305.5%
 
r2305.5%
 
C2305.5%
 
e2305.5%
 
l2305.5%
 
g2305.5%
 
F2305.5%
 
a2305.5%
 
I1794.3%
 
O511.2%
 
u511.2%
 
t511.2%
 
,90.2%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter304172.4%
 
Uppercase Letter69016.4%
 
Space Separator46011.0%
 
Other Punctuation90.2%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
C23033.3%
 
F23033.3%
 
I17925.9%
 
O517.4%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n63921.0%
 
o46015.1%
 
i46015.1%
 
d2307.6%
 
r2307.6%
 
e2307.6%
 
l2307.6%
 
g2307.6%
 
a2307.6%
 
u511.7%
 
t511.7%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
460100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
,9100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin373188.8%
 
Common46911.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n63917.1%
 
o46012.3%
 
i46012.3%
 
d2306.2%
 
r2306.2%
 
C2306.2%
 
e2306.2%
 
l2306.2%
 
g2306.2%
 
F2306.2%
 
a2306.2%
 
I1794.8%
 
O511.4%
 
u511.4%
 
t511.4%
 

Most frequent Common characters

ValueCountFrequency (%) 
46098.1%
 
,91.9%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII4200100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n63915.2%
 
o46011.0%
 
46011.0%
 
i46011.0%
 
d2305.5%
 
r2305.5%
 
C2305.5%
 
e2305.5%
 
l2305.5%
 
g2305.5%
 
F2305.5%
 
a2305.5%
 
I1794.3%
 
O511.2%
 
u511.2%
 
t511.2%
 
,90.2%
 

Product Type
Categorical

Distinct6
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Standard Fan with Light Kit
123 
Standard Fan Only
60 
Low-Mount HSSD Fan Only
15 
Hugger Fan with Light Kit
 
11
Low-Mount HSSD Fan with Light Kit
 
7
ValueCountFrequency (%) 
Standard Fan with Light Kit12355.7%
 
Standard Fan Only6027.1%
 
Low-Mount HSSD Fan Only156.8%
 
Hugger Fan with Light Kit115.0%
 
Low-Mount HSSD Fan with Light Kit73.2%
 
Hugger Fan Only52.3%
 
2020-12-12T20:00:04.341892image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:00:04.392435image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:00:04.466999image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length33
Median length27
Mean length23.83257919
Min length15

Overview of Unicode Properties

Unique unicode characters24
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
74614.2%
 
t62811.9%
 
a58711.1%
 
n5069.6%
 
i4238.0%
 
d3666.9%
 
h2825.4%
 
S2274.3%
 
F2214.2%
 
r1993.8%
 
g1733.3%
 
w1633.1%
 
L1633.1%
 
K1412.7%
 
O801.5%
 
l801.5%
 
y801.5%
 
o440.8%
 
H380.7%
 
u380.7%
 
-220.4%
 
M220.4%
 
D220.4%
 
e160.3%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter358568.1%
 
Uppercase Letter91417.4%
 
Space Separator74614.2%
 
Dash Punctuation220.4%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
S22724.8%
 
F22124.2%
 
L16317.8%
 
K14115.4%
 
O808.8%
 
H384.2%
 
M222.4%
 
D222.4%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
t62817.5%
 
a58716.4%
 
n50614.1%
 
i42311.8%
 
d36610.2%
 
h2827.9%
 
r1995.6%
 
g1734.8%
 
w1634.5%
 
l802.2%
 
y802.2%
 
o441.2%
 
u381.1%
 
e160.4%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
746100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-22100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin449985.4%
 
Common76814.6%
 

Most frequent Latin characters

ValueCountFrequency (%) 
t62814.0%
 
a58713.0%
 
n50611.2%
 
i4239.4%
 
d3668.1%
 
h2826.3%
 
S2275.0%
 
F2214.9%
 
r1994.4%
 
g1733.8%
 
w1633.6%
 
L1633.6%
 
K1413.1%
 
O801.8%
 
l801.8%
 
y801.8%
 
o441.0%
 
H380.8%
 
u380.8%
 
M220.5%
 
D220.5%
 
e160.4%
 

Most frequent Common characters

ValueCountFrequency (%) 
74697.1%
 
-222.9%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII5267100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
74614.2%
 
t62811.9%
 
a58711.1%
 
n5069.6%
 
i4238.0%
 
d3666.9%
 
h2825.4%
 
S2274.3%
 
F2214.2%
 
r1993.8%
 
g1733.3%
 
w1633.1%
 
L1633.1%
 
K1412.7%
 
O801.5%
 
l801.5%
 
y801.5%
 
o440.8%
 
H380.7%
 
u380.7%
 
-220.4%
 
M220.4%
 
D220.4%
 
e160.3%
 

Blade Span (Diameter) (in.)
Real number (ℝ≥0)

Distinct22
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.95475113
Minimum26
Maximum84
Zeros0
Zeros (%)0.0%
Memory size1.9 KiB
2020-12-12T20:00:04.539562image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum26
5-th percentile43
Q152
median56
Q360
95-th percentile80
Maximum84
Range58
Interquartile range (IQR)8

Descriptive statistics

Standard deviation9.796926121
Coefficient of variation (CV)0.1690443998
Kurtosis1.232545929
Mean57.95475113
Median Absolute Deviation (MAD)4
Skewness0.714544894
Sum12808
Variance95.97976142
MonotocityNot monotonic
2020-12-12T20:00:04.605118image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%) 
526228.1%
 
604721.3%
 
56177.7%
 
72167.2%
 
54167.2%
 
84115.0%
 
6483.6%
 
5062.7%
 
4362.7%
 
7052.3%
 
4452.3%
 
6241.8%
 
6841.8%
 
4231.4%
 
6520.9%
 
5820.9%
 
4820.9%
 
6610.5%
 
8010.5%
 
3810.5%
 
3410.5%
 
2610.5%
 
ValueCountFrequency (%) 
2610.5%
 
3410.5%
 
3810.5%
 
4231.4%
 
4362.7%
 
4452.3%
 
4820.9%
 
5062.7%
 
526228.1%
 
54167.2%
 
ValueCountFrequency (%) 
84115.0%
 
8010.5%
 
72167.2%
 
7052.3%
 
6841.8%
 
6610.5%
 
6520.9%
 
6483.6%
 
6241.8%
 
604721.3%
 

Ceiling Fan Efficiency (CFM/W)
Real number (ℝ≥0)

Distinct158
Distinct (%)71.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean244.7054299
Minimum47.4
Maximum431
Zeros0
Zeros (%)0.0%
Memory size1.9 KiB
2020-12-12T20:00:04.685688image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum47.4
5-th percentile118
Q1192
median232
Q3305
95-th percentile374.4
Maximum431
Range383.6
Interquartile range (IQR)113

Descriptive statistics

Standard deviation76.40853634
Coefficient of variation (CV)0.3122469999
Kurtosis-0.4241584072
Mean244.7054299
Median Absolute Deviation (MAD)53.2
Skewness0.1766682535
Sum54079.9
Variance5838.264425
MonotocityNot monotonic
2020-12-12T20:00:04.774764image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
11873.2%
 
20741.8%
 
155.141.8%
 
32841.8%
 
36841.8%
 
30731.4%
 
21531.4%
 
29431.4%
 
25931.4%
 
33831.4%
 
26431.4%
 
30520.9%
 
22620.9%
 
23320.9%
 
23220.9%
 
35320.9%
 
17120.9%
 
26320.9%
 
31420.9%
 
40920.9%
 
34220.9%
 
24820.9%
 
23620.9%
 
31620.9%
 
20120.9%
 
Other values (133)15268.8%
 
ValueCountFrequency (%) 
47.410.5%
 
61.610.5%
 
6710.5%
 
101.610.5%
 
11010.5%
 
11210.5%
 
11873.2%
 
12110.5%
 
12410.5%
 
133.610.5%
 
ValueCountFrequency (%) 
43110.5%
 
42010.5%
 
40920.9%
 
40010.5%
 
38520.9%
 
38210.5%
 
37820.9%
 
37510.5%
 
374.410.5%
 
37210.5%
 

Fan Power Consumption-Low Speed (W)
Real number (ℝ≥0)

MISSING

Distinct48
Distinct (%)24.9%
Missing28
Missing (%)12.7%
Infinite0
Infinite (%)0.0%
Mean3.804145078
Minimum1.7
Maximum12.8
Zeros0
Zeros (%)0.0%
Memory size1.9 KiB
2020-12-12T20:00:04.866843image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1.7
5-th percentile1.9
Q12.6
median3.3
Q34.3
95-th percentile9.6
Maximum12.8
Range11.1
Interquartile range (IQR)1.7

Descriptive statistics

Standard deviation2.050072006
Coefficient of variation (CV)0.5389047904
Kurtosis5.028271928
Mean3.804145078
Median Absolute Deviation (MAD)0.8
Skewness2.163537157
Sum734.2
Variance4.202795229
MonotocityNot monotonic
2020-12-12T20:00:04.951916image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%) 
2.7125.4%
 
2.6115.0%
 
3.7104.5%
 
3.894.1%
 
1.994.1%
 
2.194.1%
 
3.183.6%
 
2.283.6%
 
2.373.2%
 
4.373.2%
 
3.652.3%
 
252.3%
 
3.552.3%
 
3.452.3%
 
4.152.3%
 
2.852.3%
 
2.952.3%
 
341.8%
 
3.341.8%
 
10.741.8%
 
2.541.8%
 
4.741.8%
 
10.431.4%
 
6.931.4%
 
1.831.4%
 
Other values (23)3917.6%
 
(Missing)2812.7%
 
ValueCountFrequency (%) 
1.710.5%
 
1.831.4%
 
1.994.1%
 
252.3%
 
2.194.1%
 
2.283.6%
 
2.373.2%
 
2.410.5%
 
2.541.8%
 
2.6115.0%
 
ValueCountFrequency (%) 
12.810.5%
 
10.741.8%
 
10.431.4%
 
10.310.5%
 
9.910.5%
 
9.410.5%
 
6.931.4%
 
6.810.5%
 
6.520.9%
 
6.420.9%
 
Distinct144
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.86108597
Minimum10.6
Maximum82
Zeros0
Zeros (%)0.0%
Memory size1.9 KiB
2020-12-12T20:00:05.038992image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum10.6
5-th percentile16.3
Q125.1
median31.4
Q336.4
95-th percentile50.3
Maximum82
Range71.4
Interquartile range (IQR)11.3

Descriptive statistics

Standard deviation10.76076741
Coefficient of variation (CV)0.3377401328
Kurtosis3.251375579
Mean31.86108597
Median Absolute Deviation (MAD)5.6
Skewness1.168598786
Sum7041.3
Variance115.7941152
MonotocityNot monotonic
2020-12-12T20:00:05.122564image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
31.352.3%
 
24.452.3%
 
49.841.8%
 
32.341.8%
 
31.441.8%
 
28.641.8%
 
3341.8%
 
36.441.8%
 
40.631.4%
 
24.531.4%
 
22.231.4%
 
35.331.4%
 
50.331.4%
 
26.931.4%
 
20.731.4%
 
20.331.4%
 
35.431.4%
 
39.231.4%
 
30.331.4%
 
30.920.9%
 
21.420.9%
 
27.120.9%
 
31.220.9%
 
40.220.9%
 
14.920.9%
 
Other values (119)14264.3%
 
ValueCountFrequency (%) 
10.620.9%
 
11.920.9%
 
14.520.9%
 
14.920.9%
 
15.510.5%
 
15.610.5%
 
15.710.5%
 
16.310.5%
 
16.710.5%
 
16.810.5%
 
ValueCountFrequency (%) 
8210.5%
 
72.910.5%
 
67.210.5%
 
65.310.5%
 
63.410.5%
 
62.310.5%
 
58.910.5%
 
53.710.5%
 
52.410.5%
 
52.110.5%
 

Fan Power Consumption-Standby (W)
Real number (ℝ≥0)

ZEROS

Distinct21
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.135746606
Minimum0
Maximum37.3
Zeros22
Zeros (%)10.0%
Memory size1.9 KiB
2020-12-12T20:00:05.202132image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.8
median1
Q31.3
95-th percentile1.8
Maximum37.3
Range37.3
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation2.491720473
Coefficient of variation (CV)2.193905277
Kurtosis204.2376221
Mean1.135746606
Median Absolute Deviation (MAD)0.3
Skewness14.0134273
Sum251
Variance6.208670917
MonotocityNot monotonic
2020-12-12T20:00:05.270691image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%) 
0.94018.1%
 
1.22410.9%
 
02210.0%
 
1188.1%
 
1.4188.1%
 
1.3177.7%
 
0.8156.8%
 
1.1115.0%
 
0.494.1%
 
0.783.6%
 
1.862.7%
 
1.652.3%
 
0.352.3%
 
0.552.3%
 
1.941.8%
 
241.8%
 
1.541.8%
 
1.731.4%
 
0.210.5%
 
37.310.5%
 
0.610.5%
 
ValueCountFrequency (%) 
02210.0%
 
0.210.5%
 
0.352.3%
 
0.494.1%
 
0.552.3%
 
0.610.5%
 
0.783.6%
 
0.8156.8%
 
0.94018.1%
 
1188.1%
 
ValueCountFrequency (%) 
37.310.5%
 
241.8%
 
1.941.8%
 
1.862.7%
 
1.731.4%
 
1.652.3%
 
1.541.8%
 
1.4188.1%
 
1.3177.7%
 
1.22410.9%
 

Ceiling Fan Features
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)0.9%
Missing5
Missing (%)2.3%
Memory size1.9 KiB
None
192 
Occupancy sensor
24 
ValueCountFrequency (%) 
None19286.9%
 
Occupancy sensor2410.9%
 
(Missing)52.3%
 
2020-12-12T20:00:05.350260image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:00:05.396299image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:00:05.448344image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length16
Median length4
Mean length5.280542986
Min length3

Overview of Unicode Properties

Unique unicode characters13
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n25021.4%
 
o21618.5%
 
e21618.5%
 
N19216.5%
 
c726.2%
 
s484.1%
 
a292.5%
 
O242.1%
 
u242.1%
 
p242.1%
 
y242.1%
 
242.1%
 
r242.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter92779.4%
 
Uppercase Letter21618.5%
 
Space Separator242.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
N19288.9%
 
O2411.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n25027.0%
 
o21623.3%
 
e21623.3%
 
c727.8%
 
s485.2%
 
a293.1%
 
u242.6%
 
p242.6%
 
y242.6%
 
r242.6%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
24100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin114397.9%
 
Common242.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n25021.9%
 
o21618.9%
 
e21618.9%
 
N19216.8%
 
c726.3%
 
s484.2%
 
a292.5%
 
O242.1%
 
u242.1%
 
p242.1%
 
y242.1%
 
r242.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
24100.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1167100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n25021.4%
 
o21618.5%
 
e21618.5%
 
N19216.5%
 
c726.2%
 
s484.1%
 
a292.5%
 
O242.1%
 
u242.1%
 
p242.1%
 
y242.1%
 
242.1%
 
r242.1%
 
Distinct6
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
3
198 
5
 
11
One
 
5
Unlimited
 
3
3 years
 
3
ValueCountFrequency (%) 
319889.6%
 
5115.0%
 
One52.3%
 
Unlimited31.4%
 
3 years31.4%
 
110.5%
 
2020-12-12T20:00:05.525410image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)0.5%
2020-12-12T20:00:05.575954image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:00:05.643011image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length9
Median length1
Mean length1.235294118
Min length1

Overview of Unicode Properties

Unique unicode characters17
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
320173.6%
 
5114.0%
 
e114.0%
 
n82.9%
 
i62.2%
 
O51.8%
 
U31.1%
 
l31.1%
 
m31.1%
 
t31.1%
 
d31.1%
 
31.1%
 
y31.1%
 
a31.1%
 
r31.1%
 
s31.1%
 
110.4%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number21378.0%
 
Lowercase Letter4917.9%
 
Uppercase Letter82.9%
 
Space Separator31.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
320194.4%
 
5115.2%
 
110.5%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
O562.5%
 
U337.5%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
e1122.4%
 
n816.3%
 
i612.2%
 
l36.1%
 
m36.1%
 
t36.1%
 
d36.1%
 
y36.1%
 
a36.1%
 
r36.1%
 
s36.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
3100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common21679.1%
 
Latin5720.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
320193.1%
 
5115.1%
 
31.4%
 
110.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
e1119.3%
 
n814.0%
 
i610.5%
 
O58.8%
 
U35.3%
 
l35.3%
 
m35.3%
 
t35.3%
 
d35.3%
 
y35.3%
 
a35.3%
 
r35.3%
 
s35.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII273100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
320173.6%
 
5114.0%
 
e114.0%
 
n82.9%
 
i62.2%
 
O51.8%
 
U31.1%
 
l31.1%
 
m31.1%
 
t31.1%
 
d31.1%
 
31.1%
 
y31.1%
 
a31.1%
 
r31.1%
 
s31.1%
 
110.4%
 
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
No
203 
Yes
 
18
ValueCountFrequency (%) 
No20391.9%
 
Yes188.1%
 
2020-12-12T20:00:05.696057image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

ENERGY STAR Lamp ESUID
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)38.9%
Missing203
Missing (%)91.9%
Infinite0
Infinite (%)0.0%
Mean2322172.389
Minimum2308819
Maximum2346162
Zeros0
Zeros (%)0.0%
Memory size1.9 KiB
2020-12-12T20:00:05.738594image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum2308819
5-th percentile2308819
Q12308819
median2325901
Q32332621
95-th percentile2340454.25
Maximum2346162
Range37343
Interquartile range (IQR)23802

Descriptive statistics

Standard deviation13183.47749
Coefficient of variation (CV)0.005677217397
Kurtosis-1.483806003
Mean2322172.389
Median Absolute Deviation (MAD)15314
Skewness0.2128504096
Sum41799103
Variance173804078.6
MonotocityNot monotonic
2020-12-12T20:00:05.802148image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
230881983.6%
 
233262131.4%
 
232590120.9%
 
232792420.9%
 
233742910.5%
 
233944710.5%
 
234616210.5%
 
(Missing)20391.9%
 
ValueCountFrequency (%) 
230881983.6%
 
232590120.9%
 
232792420.9%
 
233262131.4%
 
233742910.5%
 
233944710.5%
 
234616210.5%
 
ValueCountFrequency (%) 
234616210.5%
 
233944710.5%
 
233742910.5%
 
233262131.4%
 
232792420.9%
 
232590120.9%
 
230881983.6%
 

Alternate ENERGY STAR Lamps ESUIDs
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing221
Missing (%)100.0%
Memory size1.9 KiB

ENERGY STAR Lamp Partner
Categorical

HIGH CORRELATION
MISSING

Distinct28
Distinct (%)19.9%
Missing80
Missing (%)36.2%
Memory size1.9 KiB
Paragon Semiconductor Lighting Technology Co., Ltd.
35 
Seoul Demiconductor Co., Ltd
13 
The Home Depot
Delta T LLC dba Big Ass Fans
Shenzhen MTC Lighting Co., Ltd.
Other values (23)
66 
ValueCountFrequency (%) 
Paragon Semiconductor Lighting Technology Co., Ltd.3515.8%
 
Seoul Demiconductor Co., Ltd135.9%
 
The Home Depot94.1%
 
Delta T LLC dba Big Ass Fans94.1%
 
Shenzhen MTC Lighting Co., Ltd.94.1%
 
Seoul Semiconductor Co., Ltd73.2%
 
Osram Opto Semiconductors73.2%
 
FUJIAN LIGHTNING OPTOELECTRONIC CO.,LTD73.2%
 
Bridgelux Inc.62.7%
 
Seoul Semiconductor Co., Ltd.41.8%
 
WAC Lighting Co41.8%
 
Semiconductor Lighting Technology Co., Ltd.41.8%
 
XuYu Optoelectronics (Shenzhen) Co., Ltd.31.4%
 
FUJIAN LIGHTNING OPTOELECTRONIC CO., LTD31.4%
 
Ellen Lighting, Inc31.4%
 
Generation Brands20.9%
 
Guangzhou Hongli Opto-Electronic Co., Ltd.20.9%
 
Cree, Inc.20.9%
 
Maxlite20.9%
 
Samsung Electronics LED Business20.9%
 
Samsung Electronics Co., Ltd10.5%
 
Edison Opto Corporation10.5%
 
Seoul Semiconductor10.5%
 
Hongli Zhihui Group Co.,Ltd.10.5%
 
Fujian Lighting Optoelectronic Co.,Ltd Shenzhen Branch10.5%
 
Other values (3)31.4%
 
(Missing)8036.2%
 
2020-12-12T20:00:05.891225image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique8 ?
Unique (%)5.7%
2020-12-12T20:00:05.974297image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length57
Median length25
Mean length22.21266968
Min length3

Overview of Unicode Properties

Unique unicode characters51
Unique unicode categories7 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
49310.0%
 
n4529.2%
 
o4258.7%
 
t2645.4%
 
e2394.9%
 
i2314.7%
 
g2184.4%
 
c2144.4%
 
a2034.1%
 
L1913.9%
 
d1713.5%
 
.1593.2%
 
r1422.9%
 
h1422.9%
 
C1412.9%
 
u1232.5%
 
T1062.2%
 
S1002.0%
 
l1002.0%
 
,962.0%
 
m901.8%
 
O621.3%
 
s611.2%
 
I511.0%
 
P450.9%
 
Other values (26)3907.9%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter317664.7%
 
Uppercase Letter97719.9%
 
Space Separator49310.0%
 
Other Punctuation2555.2%
 
Open Punctuation30.1%
 
Close Punctuation30.1%
 
Dash Punctuation2< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
L19119.5%
 
C14114.4%
 
T10610.8%
 
S10010.2%
 
O626.3%
 
I515.2%
 
P454.6%
 
D444.5%
 
N404.1%
 
E313.2%
 
G252.6%
 
A232.4%
 
H222.3%
 
B212.1%
 
F212.1%
 
M111.1%
 
U101.0%
 
J101.0%
 
R101.0%
 
W50.5%
 
X30.3%
 
Y30.3%
 
Z10.1%
 
K10.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n45214.2%
 
o42513.4%
 
t2648.3%
 
e2397.5%
 
i2317.3%
 
g2186.9%
 
c2146.7%
 
a2036.4%
 
d1715.4%
 
r1424.5%
 
h1424.5%
 
u1233.9%
 
l1003.1%
 
m902.8%
 
s611.9%
 
y391.2%
 
p270.9%
 
z160.5%
 
b90.3%
 
x80.3%
 
j20.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
493100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.15962.4%
 
,9637.6%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-2100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(3100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)3100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin415384.6%
 
Common75615.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n45210.9%
 
o42510.2%
 
t2646.4%
 
e2395.8%
 
i2315.6%
 
g2185.2%
 
c2145.2%
 
a2034.9%
 
L1914.6%
 
d1714.1%
 
r1423.4%
 
h1423.4%
 
C1413.4%
 
u1233.0%
 
T1062.6%
 
S1002.4%
 
l1002.4%
 
m902.2%
 
O621.5%
 
s611.5%
 
I511.2%
 
P451.1%
 
D441.1%
 
N401.0%
 
y390.9%
 
Other values (20)2596.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
49365.2%
 
.15921.0%
 
,9612.7%
 
(30.4%
 
)30.4%
 
-20.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII4909100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
49310.0%
 
n4529.2%
 
o4258.7%
 
t2645.4%
 
e2394.9%
 
i2314.7%
 
g2184.4%
 
c2144.4%
 
a2034.1%
 
L1913.9%
 
d1713.5%
 
.1593.2%
 
r1422.9%
 
h1422.9%
 
C1412.9%
 
u1232.5%
 
T1062.2%
 
S1002.0%
 
l1002.0%
 
,962.0%
 
m901.8%
 
O621.3%
 
s611.2%
 
I511.0%
 
P450.9%
 
Other values (26)3907.9%
 

Lamp Model Number
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)33.3%
Missing203
Missing (%)91.9%
Memory size1.9 KiB
1002863140
9W-A19E26-LED-30K
E9A19D930/JA8
97502S
51331
ValueCountFrequency (%) 
100286314094.1%
 
9W-A19E26-LED-30K31.4%
 
E9A19D930/JA820.9%
 
97502S20.9%
 
5133110.5%
 
E26A19-9.5D-27210-B462-0010.5%
 
(Missing)20391.9%
 
2020-12-12T20:00:06.056868image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)11.1%
2020-12-12T20:00:06.110414image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:00:06.178472image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length25
Median length3
Mean length3.701357466
Min length3

Overview of Unicode Properties

Unique unicode characters24
Unique unicode categories5 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n40649.6%
 
a20324.8%
 
0374.5%
 
1273.3%
 
2182.2%
 
9162.0%
 
3162.0%
 
6141.7%
 
-131.6%
 
8111.3%
 
4101.2%
 
E91.1%
 
A81.0%
 
D60.7%
 
540.5%
 
730.4%
 
W30.4%
 
L30.4%
 
K30.4%
 
S20.2%
 
/20.2%
 
J20.2%
 
.10.1%
 
B10.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter60974.4%
 
Decimal Number15619.1%
 
Uppercase Letter374.5%
 
Dash Punctuation131.6%
 
Other Punctuation30.4%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n40666.7%
 
a20333.3%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03723.7%
 
12717.3%
 
21811.5%
 
91610.3%
 
31610.3%
 
6149.0%
 
8117.1%
 
4106.4%
 
542.6%
 
731.9%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E924.3%
 
A821.6%
 
D616.2%
 
W38.1%
 
L38.1%
 
K38.1%
 
S25.4%
 
J25.4%
 
B12.7%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/266.7%
 
.133.3%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-13100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin64679.0%
 
Common17221.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n40662.8%
 
a20331.4%
 
E91.4%
 
A81.2%
 
D60.9%
 
W30.5%
 
L30.5%
 
K30.5%
 
S20.3%
 
J20.3%
 
B10.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
03721.5%
 
12715.7%
 
21810.5%
 
9169.3%
 
3169.3%
 
6148.1%
 
-137.6%
 
8116.4%
 
4105.8%
 
542.3%
 
731.7%
 
/21.2%
 
.10.6%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII818100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n40649.6%
 
a20324.8%
 
0374.5%
 
1273.3%
 
2182.2%
 
9162.0%
 
3162.0%
 
6141.7%
 
-131.6%
 
8111.3%
 
4101.2%
 
E91.1%
 
A81.0%
 
D60.7%
 
540.5%
 
730.4%
 
W30.4%
 
L30.4%
 
K30.4%
 
S20.2%
 
/20.2%
 
J20.2%
 
.10.1%
 
B10.1%
 

Light Source Technology
Categorical

MISSING

Distinct1
Distinct (%)5.6%
Missing203
Missing (%)91.9%
Memory size1.9 KiB
LED
18 
ValueCountFrequency (%) 
LED188.1%
 
(Missing)20391.9%
 
2020-12-12T20:00:06.247031image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:00:06.288567image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:00:06.329602image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Overview of Unicode Properties

Unique unicode characters5
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n40661.2%
 
a20330.6%
 
L182.7%
 
E182.7%
 
D182.7%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter60991.9%
 
Uppercase Letter548.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n40666.7%
 
a20333.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
L1833.3%
 
E1833.3%
 
D1833.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin663100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n40661.2%
 
a20330.6%
 
L182.7%
 
E182.7%
 
D182.7%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII663100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n40661.2%
 
a20330.6%
 
L182.7%
 
E182.7%
 
D182.7%
 

Total Light Output (lumens)
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct42
Distinct (%)29.8%
Missing80
Missing (%)36.2%
Infinite0
Infinite (%)0.0%
Mean1305.64539
Minimum800
Maximum2800
Zeros0
Zeros (%)0.0%
Memory size1.9 KiB
2020-12-12T20:00:06.399162image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum800
5-th percentile800
Q11050
median1210
Q31440
95-th percentile2200
Maximum2800
Range2000
Interquartile range (IQR)390

Descriptive statistics

Standard deviation418.6920473
Coefficient of variation (CV)0.3206782259
Kurtosis2.24277241
Mean1305.64539
Median Absolute Deviation (MAD)230
Skewness1.33976045
Sum184096
Variance175303.0305
MonotocityNot monotonic
2020-12-12T20:00:06.478730image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%) 
800167.2%
 
1440125.4%
 
121094.1%
 
120094.1%
 
85094.1%
 
118083.6%
 
177083.6%
 
100062.7%
 
110062.7%
 
160052.3%
 
220052.3%
 
117041.8%
 
122731.4%
 
124031.4%
 
105031.4%
 
131031.4%
 
127620.9%
 
147020.9%
 
165320.9%
 
115020.9%
 
280020.9%
 
81020.9%
 
135210.5%
 
147910.5%
 
190010.5%
 
Other values (17)177.7%
 
(Missing)8036.2%
 
ValueCountFrequency (%) 
800167.2%
 
81020.9%
 
85094.1%
 
100062.7%
 
105031.4%
 
110062.7%
 
115020.9%
 
117041.8%
 
118083.6%
 
119810.5%
 
ValueCountFrequency (%) 
280020.9%
 
270010.5%
 
235010.5%
 
230410.5%
 
220052.3%
 
214510.5%
 
190010.5%
 
177083.6%
 
170010.5%
 
165610.5%
 

Total Lighting Input Power (Watts)
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct19
Distinct (%)13.5%
Missing80
Missing (%)36.2%
Infinite0
Infinite (%)0.0%
Mean17.38723404
Minimum9
Maximum40
Zeros0
Zeros (%)0.0%
Memory size1.9 KiB
2020-12-12T20:00:06.557298image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile9.3
Q115
median18
Q320
95-th percentile25.5
Maximum40
Range31
Interquartile range (IQR)5

Descriptive statistics

Standard deviation5.447199163
Coefficient of variation (CV)0.3132872744
Kurtosis3.020929691
Mean17.38723404
Median Absolute Deviation (MAD)2
Skewness0.9092213336
Sum2451.6
Variance29.67197872
MonotocityNot monotonic
2020-12-12T20:00:06.621854image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%) 
184721.3%
 
20188.1%
 
15135.9%
 
16104.5%
 
9.5104.5%
 
1094.1%
 
25.583.6%
 
2573.2%
 
962.7%
 
4020.9%
 
9.320.9%
 
1420.9%
 
17.510.5%
 
15.710.5%
 
3010.5%
 
1710.5%
 
23.610.5%
 
2610.5%
 
16.210.5%
 
(Missing)8036.2%
 
ValueCountFrequency (%) 
962.7%
 
9.320.9%
 
9.5104.5%
 
1094.1%
 
1420.9%
 
15135.9%
 
15.710.5%
 
16104.5%
 
16.210.5%
 
1710.5%
 
ValueCountFrequency (%) 
4020.9%
 
3010.5%
 
2610.5%
 
25.583.6%
 
2573.2%
 
23.610.5%
 
20188.1%
 
184721.3%
 
17.510.5%
 
1710.5%
 
Missing221
Missing (%)100.0%
Memory size1.9 KiB

Lighting Efficiency – Measured at the Source (lm/W)
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing221
Missing (%)100.0%
Memory size1.9 KiB

Power Factor of Light Kit
Real number (ℝ≥0)

MISSING

Distinct17
Distinct (%)12.1%
Missing80
Missing (%)36.2%
Infinite0
Infinite (%)0.0%
Mean0.9154609929
Minimum0.6
Maximum1
Zeros0
Zeros (%)0.0%
Memory size1.9 KiB
2020-12-12T20:00:06.694416image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile0.7
Q10.9
median0.95
Q30.97
95-th percentile0.99
Maximum1
Range0.4
Interquartile range (IQR)0.07

Descriptive statistics

Standard deviation0.08606870327
Coefficient of variation (CV)0.09401678928
Kurtosis3.843409296
Mean0.9154609929
Median Absolute Deviation (MAD)0.03
Skewness-2.053662618
Sum129.08
Variance0.007407821682
MonotocityNot monotonic
2020-12-12T20:00:06.764977image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%) 
0.953013.6%
 
0.97209.0%
 
0.9209.0%
 
0.96156.8%
 
0.98115.0%
 
0.794.1%
 
0.9983.6%
 
0.8862.7%
 
0.841.8%
 
0.8231.4%
 
0.631.4%
 
0.9131.4%
 
0.9431.4%
 
0.9220.9%
 
0.8920.9%
 
110.5%
 
0.8710.5%
 
(Missing)8036.2%
 
ValueCountFrequency (%) 
0.631.4%
 
0.794.1%
 
0.841.8%
 
0.8231.4%
 
0.8710.5%
 
0.8862.7%
 
0.8920.9%
 
0.9209.0%
 
0.9131.4%
 
0.9220.9%
 
ValueCountFrequency (%) 
110.5%
 
0.9983.6%
 
0.98115.0%
 
0.97209.0%
 
0.96156.8%
 
0.953013.6%
 
0.9431.4%
 
0.9220.9%
 
0.9131.4%
 
0.9209.0%
 

Light Color Appearance (CCT)
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)4.3%
Missing80
Missing (%)36.2%
Memory size1.9 KiB
3000K
112 
2700K
16 
4000/4100K
 
9
2700K,3000K,5000K
 
2
3500K
 
1
ValueCountFrequency (%) 
3000K11250.7%
 
2700K167.2%
 
4000/4100K94.1%
 
2700K,3000K,5000K20.9%
 
3500K10.5%
 
2700K,4000/4100K10.5%
 
(Missing)8036.2%
 
2020-12-12T20:00:06.844045image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)1.4%
2020-12-12T20:00:06.890085image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:00:06.957643image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length17
Median length5
Mean length4.63800905
Min length3

Overview of Unicode Properties

Unique unicode characters12
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
043842.7%
 
n16015.6%
 
K14614.2%
 
311511.2%
 
a807.8%
 
4202.0%
 
2191.9%
 
7191.9%
 
/101.0%
 
1101.0%
 
,50.5%
 
530.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number62460.9%
 
Lowercase Letter24023.4%
 
Uppercase Letter14614.2%
 
Other Punctuation151.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
043870.2%
 
311518.4%
 
4203.2%
 
2193.0%
 
7193.0%
 
1101.6%
 
530.5%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
K146100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n16066.7%
 
a8033.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/1066.7%
 
,533.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common63962.3%
 
Latin38637.7%
 

Most frequent Common characters

ValueCountFrequency (%) 
043868.5%
 
311518.0%
 
4203.1%
 
2193.0%
 
7193.0%
 
/101.6%
 
1101.6%
 
,50.8%
 
530.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n16041.5%
 
K14637.8%
 
a8020.7%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1025100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
043842.7%
 
n16015.6%
 
K14614.2%
 
311511.2%
 
a807.8%
 
4202.0%
 
2191.9%
 
7191.9%
 
/101.0%
 
1101.0%
 
,50.5%
 
530.3%
 

Light Color Quality (CRI)
Real number (ℝ≥0)

MISSING

Distinct10
Distinct (%)7.1%
Missing80
Missing (%)36.2%
Infinite0
Infinite (%)0.0%
Mean91.36879433
Minimum81
Maximum95
Zeros0
Zeros (%)0.0%
Memory size1.9 KiB
2020-12-12T20:00:07.021698image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum81
5-th percentile82
Q192
median93
Q393
95-th percentile95
Maximum95
Range14
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.935935807
Coefficient of variation (CV)0.04307746246
Kurtosis1.599713278
Mean91.36879433
Median Absolute Deviation (MAD)1
Skewness-1.753554142
Sum12883
Variance15.49159068
MonotocityNot monotonic
2020-12-12T20:00:07.079248image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
935725.8%
 
94219.5%
 
92198.6%
 
82167.2%
 
91125.4%
 
95104.5%
 
8320.9%
 
8720.9%
 
8110.5%
 
8510.5%
 
(Missing)8036.2%
 
ValueCountFrequency (%) 
8110.5%
 
82167.2%
 
8320.9%
 
8510.5%
 
8720.9%
 
91125.4%
 
92198.6%
 
935725.8%
 
94219.5%
 
95104.5%
 
ValueCountFrequency (%) 
95104.5%
 
94219.5%
 
935725.8%
 
92198.6%
 
91125.4%
 
8720.9%
 
8510.5%
 
8320.9%
 
82167.2%
 
8110.5%
 

Light Source Rated Life (Hours)
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)7.1%
Missing80
Missing (%)36.2%
Memory size1.9 KiB
36,000
46 
54,000
34 
50,000
17 
15000
12 
48,000
Other values (5)
23 
ValueCountFrequency (%) 
36,0004620.8%
 
54,0003415.4%
 
50,000177.7%
 
15000125.4%
 
48,00094.1%
 
60,00073.2%
 
2500062.7%
 
25,00062.7%
 
72,00031.4%
 
30,00010.5%
 
(Missing)8036.2%
 
2020-12-12T20:00:07.154812image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)0.7%
2020-12-12T20:00:07.206357image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:00:07.285425image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length6
Mean length4.832579186
Min length3

Overview of Unicode Properties

Unique unicode characters12
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
044841.9%
 
n16015.0%
 
,12311.5%
 
a807.5%
 
5757.0%
 
6535.0%
 
3474.4%
 
4434.0%
 
2151.4%
 
1121.1%
 
890.8%
 
730.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number70566.0%
 
Lowercase Letter24022.5%
 
Other Punctuation12311.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
044863.5%
 
57510.6%
 
6537.5%
 
3476.7%
 
4436.1%
 
2152.1%
 
1121.7%
 
891.3%
 
730.4%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
,123100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n16066.7%
 
a8033.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common82877.5%
 
Latin24022.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
044854.1%
 
,12314.9%
 
5759.1%
 
6536.4%
 
3475.7%
 
4435.2%
 
2151.8%
 
1121.4%
 
891.1%
 
730.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n16066.7%
 
a8033.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1068100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
044841.9%
 
n16015.0%
 
,12311.5%
 
a807.5%
 
5757.0%
 
6535.0%
 
3474.4%
 
4434.0%
 
2151.4%
 
1121.1%
 
890.8%
 
730.3%
 

Light Sources Per Light Kit
Categorical

MISSING

Distinct2
Distinct (%)11.1%
Missing203
Missing (%)91.9%
Memory size1.9 KiB
2
11 
3
ValueCountFrequency (%) 
2115.0%
 
373.2%
 
(Missing)20391.9%
 
2020-12-12T20:00:07.362491image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:00:07.411533image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:00:07.456071image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n40661.2%
 
a20330.6%
 
.182.7%
 
0182.7%
 
2111.7%
 
371.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter60991.9%
 
Decimal Number365.4%
 
Other Punctuation182.7%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n40666.7%
 
a20333.3%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
01850.0%
 
21130.6%
 
3719.4%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.18100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin60991.9%
 
Common548.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n40666.7%
 
a20333.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
.1833.3%
 
01833.3%
 
21120.4%
 
3713.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII663100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n40661.2%
 
a20330.6%
 
.182.7%
 
0182.7%
 
2111.7%
 
371.1%
 
Distinct1
Distinct (%)5.6%
Missing203
Missing (%)91.9%
Memory size1.9 KiB
E26
18 
ValueCountFrequency (%) 
E26188.1%
 
(Missing)20391.9%
 
2020-12-12T20:00:07.521127image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:00:07.562663image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:00:07.603198image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Overview of Unicode Properties

Unique unicode characters5
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n40661.2%
 
a20330.6%
 
E182.7%
 
2182.7%
 
6182.7%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter60991.9%
 
Decimal Number365.4%
 
Uppercase Letter182.7%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n40666.7%
 
a20333.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E18100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
21850.0%
 
61850.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin62794.6%
 
Common365.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n40664.8%
 
a20332.4%
 
E182.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
21850.0%
 
61850.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII663100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n40661.2%
 
a20330.6%
 
E182.7%
 
2182.7%
 
6182.7%
 
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Yes
216 
No
 
5
ValueCountFrequency (%) 
Yes21697.7%
 
No52.3%
 
2020-12-12T20:00:07.646736image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Missing221
Missing (%)100.0%
Memory size1.9 KiB

Ceiling Fan Light Kit Warranty (yrs)
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing221
Missing (%)100.0%
Memory size1.9 KiB
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
No
218 
Yes
 
3
ValueCountFrequency (%) 
No21898.6%
 
Yes31.4%
 
2020-12-12T20:00:07.675761image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Connects Using
Categorical

MISSING

Distinct1
Distinct (%)100.0%
Missing220
Missing (%)99.5%
Memory size1.9 KiB
Wired Ethernet
ValueCountFrequency (%) 
Wired Ethernet10.5%
 
(Missing)22099.5%
 
2020-12-12T20:00:07.722801image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)100.0%
2020-12-12T20:00:07.766339image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:00:07.809376image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length14
Median length3
Mean length3.049773756
Min length3

Overview of Unicode Properties

Unique unicode characters11
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n44165.4%
 
a22032.6%
 
e30.4%
 
r20.3%
 
t20.3%
 
W10.1%
 
i10.1%
 
d10.1%
 
10.1%
 
E10.1%
 
h10.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter67199.6%
 
Uppercase Letter20.3%
 
Space Separator10.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n44165.7%
 
a22032.8%
 
e30.4%
 
r20.3%
 
t20.3%
 
i10.1%
 
d10.1%
 
h10.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
W150.0%
 
E150.0%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
1100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin67399.9%
 
Common10.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n44165.5%
 
a22032.7%
 
e30.4%
 
r20.3%
 
t20.3%
 
W10.1%
 
i10.1%
 
d10.1%
 
E10.1%
 
h10.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
1100.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII674100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n44165.4%
 
a22032.6%
 
e30.4%
 
r20.3%
 
t20.3%
 
W10.1%
 
i10.1%
 
d10.1%
 
10.1%
 
E10.1%
 
h10.1%
 

Notes
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing221
Missing (%)100.0%
Memory size1.9 KiB

Date Available on Market
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct62
Distinct (%)28.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
02/14/2019
24 
05/07/2019
18 
08/14/2014
 
14
03/01/2020
 
9
02/01/2020
 
9
Other values (57)
147 
ValueCountFrequency (%) 
02/14/20192410.9%
 
05/07/2019188.1%
 
08/14/2014146.3%
 
03/01/202094.1%
 
02/01/202094.1%
 
06/15/201883.6%
 
09/30/201883.6%
 
06/15/202083.6%
 
01/14/201983.6%
 
07/20/201873.2%
 
08/01/201873.2%
 
12/31/201862.7%
 
03/31/202062.7%
 
02/29/202052.3%
 
06/14/201841.8%
 
11/30/201941.8%
 
06/01/202041.8%
 
09/05/201941.8%
 
01/15/202031.4%
 
02/15/201931.4%
 
07/01/201931.4%
 
10/01/201831.4%
 
03/04/201920.9%
 
11/29/201920.9%
 
05/01/202020.9%
 
Other values (37)5022.6%
 
2020-12-12T20:00:07.893448image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique24 ?
Unique (%)10.9%
2020-12-12T20:00:07.968012image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length10
Min length10

Overview of Unicode Properties

Unique unicode characters11
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
058526.5%
 
/44220.0%
 
137416.9%
 
235916.2%
 
91145.2%
 
8833.8%
 
4753.4%
 
3632.9%
 
5532.4%
 
7321.4%
 
6301.4%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number176880.0%
 
Other Punctuation44220.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
058533.1%
 
137421.2%
 
235920.3%
 
91146.4%
 
8834.7%
 
4754.2%
 
3633.6%
 
5533.0%
 
7321.8%
 
6301.7%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/442100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common2210100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
058526.5%
 
/44220.0%
 
137416.9%
 
235916.2%
 
91145.2%
 
8833.8%
 
4753.4%
 
3632.9%
 
5532.4%
 
7321.4%
 
6301.4%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII2210100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
058526.5%
 
/44220.0%
 
137416.9%
 
235916.2%
 
91145.2%
 
8833.8%
 
4753.4%
 
3632.9%
 
5532.4%
 
7321.4%
 
6301.4%
 

Date Certified
Categorical

HIGH CARDINALITY

Distinct113
Distinct (%)51.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
06/05/2018
 
14
06/04/2020
 
9
01/02/2020
 
8
03/09/2020
 
8
06/03/2020
 
7
Other values (108)
175 
ValueCountFrequency (%) 
06/05/2018146.3%
 
06/04/202094.1%
 
01/02/202083.6%
 
03/09/202083.6%
 
06/03/202073.2%
 
01/20/201941.8%
 
09/17/201841.8%
 
01/17/201941.8%
 
05/13/201941.8%
 
05/18/202041.8%
 
02/19/201941.8%
 
07/31/201841.8%
 
05/20/202041.8%
 
05/14/201941.8%
 
09/04/201941.8%
 
02/24/201931.4%
 
08/08/201931.4%
 
11/29/201831.4%
 
05/06/202020.9%
 
08/20/201920.9%
 
01/06/201920.9%
 
02/27/202020.9%
 
06/15/201820.9%
 
10/14/201920.9%
 
04/21/202020.9%
 
Other values (88)11250.7%
 
2020-12-12T20:00:08.051584image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique64 ?
Unique (%)29.0%
2020-12-12T20:00:08.128650image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length10
Min length10

Overview of Unicode Properties

Unique unicode characters11
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
061027.6%
 
/44220.0%
 
239317.8%
 
129413.3%
 
91436.5%
 
8743.3%
 
3602.7%
 
6522.4%
 
4512.3%
 
5512.3%
 
7401.8%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number176880.0%
 
Other Punctuation44220.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
061034.5%
 
239322.2%
 
129416.6%
 
91438.1%
 
8744.2%
 
3603.4%
 
6522.9%
 
4512.9%
 
5512.9%
 
7402.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/442100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common2210100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
061027.6%
 
/44220.0%
 
239317.8%
 
129413.3%
 
91436.5%
 
8743.3%
 
3602.7%
 
6522.4%
 
4512.3%
 
5512.3%
 
7401.8%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII2210100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
061027.6%
 
/44220.0%
 
239317.8%
 
129413.3%
 
91436.5%
 
8743.3%
 
3602.7%
 
6522.4%
 
4512.3%
 
5512.3%
 
7401.8%
 

Markets
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
United States, Canada
140 
United States
81 
ValueCountFrequency (%) 
United States, Canada14063.3%
 
United States8136.7%
 
2020-12-12T20:00:08.195708image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-12T20:00:08.240246image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:00:08.294293image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length21
Median length21
Mean length18.0678733
Min length13

Overview of Unicode Properties

Unique unicode characters12
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
t66316.6%
 
a64116.1%
 
e44211.1%
 
n3619.0%
 
d3619.0%
 
3619.0%
 
U2215.5%
 
i2215.5%
 
S2215.5%
 
s2215.5%
 
,1403.5%
 
C1403.5%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter291072.9%
 
Uppercase Letter58214.6%
 
Space Separator3619.0%
 
Other Punctuation1403.5%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
U22138.0%
 
S22138.0%
 
C14024.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
t66322.8%
 
a64122.0%
 
e44215.2%
 
n36112.4%
 
d36112.4%
 
i2217.6%
 
s2217.6%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
361100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
,140100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin349287.5%
 
Common50112.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
t66319.0%
 
a64118.4%
 
e44212.7%
 
n36110.3%
 
d36110.3%
 
U2216.3%
 
i2216.3%
 
S2216.3%
 
s2216.3%
 
C1404.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
36172.1%
 
,14027.9%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII3993100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
t66316.6%
 
a64116.1%
 
e44211.1%
 
n3619.0%
 
d3619.0%
 
3619.0%
 
U2215.5%
 
i2215.5%
 
S2215.5%
 
s2215.5%
 
,1403.5%
 
C1403.5%
 

CB Model Identifier
Categorical

UNIQUE

Distinct221
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
ES_22491_F-004L_05182020064223_4143062
 
1
ES_1113298_S3150-S0-AB-04-02-C-01-F258_0605201804094370185421
 
1
ES_22491_52WAM_02032020091728_1448190
 
1
ES_1113298_S3150-A2-BC-04-02-C-01_0605201804094370185410
 
1
ES_20516_AL583KCL/CP141050XX/ 300146XXX_05202019212347_7427491
 
1
Other values (216)
216 
ValueCountFrequency (%) 
ES_22491_F-004L_05182020064223_414306210.5%
 
ES_1113298_S3150-S0-AB-04-02-C-01-F258_060520180409437018542110.5%
 
ES_22491_52WAM_02032020091728_144819010.5%
 
ES_1113298_S3150-A2-BC-04-02-C-01_060520180409437018541010.5%
 
ES_20516_AL583KCL/CP141050XX/ 300146XXX_05202019212347_742749110.5%
 
ES_20516_Lehr II_07272018123011_351803010.5%
 
ES_1113298_MK-I61-061906_03122020030215_8001388210.5%
 
ES_1023643_1097LED-**-WC_10152019055613_897387610.5%
 
ES_1113136_3TAR56***D_05132019194453_669339810.5%
 
ES_30086_RM337_06042020055333_001323010.5%
 
ES_1113136_3MAVR52*****_11292018095553_535320610.5%
 
ES_20516_300106BAP_07272018121952_977474310.5%
 
ES_1040003_MAD7997***_03202019012316_499622110.5%
 
ES_20516_300160BB_07272018115329_379589210.5%
 
ES_1040003_MAD8530*_03132019111318_559866410.5%
 
ES_1113298_MK-I61-061806_01202020044002_8001388210.5%
 
ES_1040003_MAD8530*_03132019111321_560152110.5%
 
ES_1059364_SUN505ESLED_01062020025318_919838710.5%
 
ES_31912_68-WWD_11182019014552_155227710.5%
 
ES_22491_52WAHF-L_01202020012235_335540010.5%
 
ES_1113136_56SGW-2-W_03132018154817_685039610.5%
 
ES_1023643_1055-WC_09052019031353_323315410.5%
 
ES_1122596_AE2+50LED_05152019075717_703791710.5%
 
ES_22491_FR-W1803-52L_04212020052148_650832610.5%
 
ES_1040003_LP8359*_07052018065722_384289710.5%
 
Other values (196)19688.7%
 
2020-12-12T20:00:08.382869image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique221 ?
Unique (%)100.0%
2020-12-12T20:00:08.469444image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length72
Median length42
Mean length44.29864253
Min length36

Overview of Unicode Properties

Unique unicode characters65
Unique unicode categories10 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
0148715.2%
 
1122912.6%
 
29639.8%
 
_8789.0%
 
37027.2%
 
55655.8%
 
94945.0%
 
44804.9%
 
84564.7%
 
64004.1%
 
73133.2%
 
E2642.7%
 
S2552.6%
 
-2082.1%
 
*1751.8%
 
A951.0%
 
D840.9%
 
L710.7%
 
M600.6%
 
F590.6%
 
R510.5%
 
C500.5%
 
430.4%
 
W370.4%
 
X320.3%
 
Other values (40)3393.5%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number708972.4%
 
Uppercase Letter122012.5%
 
Connector Punctuation8789.0%
 
Dash Punctuation2082.1%
 
Other Punctuation1831.9%
 
Lowercase Letter1451.5%
 
Space Separator430.4%
 
Math Symbol180.2%
 
Open Punctuation3< 0.1%
 
Close Punctuation3< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E26421.6%
 
S25520.9%
 
A957.8%
 
D846.9%
 
L715.8%
 
M604.9%
 
F594.8%
 
R514.2%
 
C504.1%
 
W373.0%
 
X322.6%
 
P252.0%
 
B242.0%
 
V181.5%
 
K181.5%
 
I181.5%
 
T110.9%
 
H100.8%
 
N90.7%
 
G80.7%
 
O70.6%
 
Z50.4%
 
U50.4%
 
Y30.2%
 
Q10.1%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_878100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
0148721.0%
 
1122917.3%
 
296313.6%
 
37029.9%
 
55658.0%
 
94947.0%
 
44806.8%
 
84566.4%
 
64005.6%
 
73134.4%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
*17595.6%
 
/73.8%
 
,10.5%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
43100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(3100.0%
 

Most frequent Math Symbol characters

ValueCountFrequency (%) 
+1372.2%
 
=316.7%
 
~211.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n2215.2%
 
r139.0%
 
a139.0%
 
g139.0%
 
o117.6%
 
t117.6%
 
u106.9%
 
i96.2%
 
m85.5%
 
k64.1%
 
d64.1%
 
b42.8%
 
e42.8%
 
h42.8%
 
s42.8%
 
l32.1%
 
p21.4%
 
c10.7%
 
y10.7%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)3100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-208100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common842586.1%
 
Latin136513.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
E26419.3%
 
S25518.7%
 
A957.0%
 
D846.2%
 
L715.2%
 
M604.4%
 
F594.3%
 
R513.7%
 
C503.7%
 
W372.7%
 
X322.3%
 
P251.8%
 
B241.8%
 
n221.6%
 
V181.3%
 
K181.3%
 
I181.3%
 
r131.0%
 
a131.0%
 
g131.0%
 
o110.8%
 
T110.8%
 
t110.8%
 
H100.7%
 
u100.7%
 
Other values (19)906.6%
 

Most frequent Common characters

ValueCountFrequency (%) 
0148717.6%
 
1122914.6%
 
296311.4%
 
_87810.4%
 
37028.3%
 
55656.7%
 
94945.9%
 
44805.7%
 
84565.4%
 
64004.7%
 
73133.7%
 
-2082.5%
 
*1752.1%
 
430.5%
 
+130.2%
 
/70.1%
 
(3< 0.1%
 
=3< 0.1%
 
)3< 0.1%
 
~2< 0.1%
 
,1< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII9790100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
0148715.2%
 
1122912.6%
 
29639.8%
 
_8789.0%
 
37027.2%
 
55655.8%
 
94945.0%
 
44804.9%
 
84564.7%
 
64004.1%
 
73133.2%
 
E2642.7%
 
S2552.6%
 
-2082.1%
 
*1751.8%
 
A951.0%
 
D840.9%
 
L710.7%
 
M600.6%
 
F590.6%
 
R510.5%
 
C500.5%
 
430.4%
 
W370.4%
 
X320.3%
 
Other values (40)3393.5%
 
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Yes
187 
No
34 
ValueCountFrequency (%) 
Yes18784.6%
 
No3415.4%
 
2020-12-12T20:00:08.526993image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Interactions

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2020-12-12T20:00:01.012026image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:00:01.074580image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Correlations

2020-12-12T20:00:08.585543image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-12-12T20:00:08.799728image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-12-12T20:00:09.016414image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-12-12T20:00:09.248114image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-12-12T20:00:09.498329image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-12-12T20:00:01.288764image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:00:02.175527image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:00:02.459772image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T20:00:02.743016image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Sample

First rows

ENERGY STAR Unique IDENERGY STAR PartnerBrand NameModel NameModel NumberAdditional Model InformationIndoor/OutdoorProduct TypeBlade Span (Diameter) (in.)Ceiling Fan Efficiency (CFM/W)Fan Power Consumption-Low Speed (W)Fan Power Consumption-High Speed (W)Fan Power Consumption-Standby (W)Ceiling Fan FeaturesCeiling Fan Components Warranty (Years)Shipped with ENERGY STAR Lamp(s)ENERGY STAR Lamp ESUIDAlternate ENERGY STAR Lamps ESUIDsENERGY STAR Lamp PartnerLamp Model NumberLight Source TechnologyTotal Light Output (lumens)Total Lighting Input Power (Watts)Lighting Efficiency – Measured outside the Fixture (lm/W)Lighting Efficiency – Measured at the Source (lm/W)Power Factor of Light KitLight Color Appearance (CCT)Light Color Quality (CRI)Light Source Rated Life (Hours)Light Sources Per Light KitLight Source Connection/Base TypeLight Kit DimmabilitySpecial Lighting Features (Dimming, Motion Sensing, etc.)Ceiling Fan Light Kit Warranty (yrs)Connected FunctionalityConnects UsingNotesDate Available on MarketDate CertifiedMarketsCB Model IdentifierMeets ENERGY STAR Most Efficient 2019 Criteria
02324807Fanimation Inc.FanimationLevon CustomMAD7912**NaNIndoor Ceiling FanStandard Fan with Light Kit72342.05.130.30.9None3NoNaNNaNParagon Semiconductor Lighting Technology Co., Ltd.NaNNaN1170.018.0NaNNaN0.953000K94.036,000NaNNaNYesNaNNaNNoNaNNaN09/01/201804/17/2019United States, CanadaES_1040003_MAD7912**_02152017053147_6707696Yes
12337073Fanimation Inc.FanimationLEVON CUSTOMMAD7912*NaNIndoor Ceiling FanStandard Fan with Light Kit52245.02.530.30.9None3NoNaNNaNParagon Semiconductor Lighting Technology Co., Ltd.NaNNaN1170.018.0NaNNaN0.953000K94.036,000NaNNaNYesNaNNaNNoNaNNaN08/31/201804/18/2019United States, CanadaES_1040003_MAD7912*_04192019101031_8631165Yes
22337112Fanimation Inc.FanimationLEVON CUSTOMMAD7912*NaNIndoor Ceiling FanStandard Fan with Light Kit64315.03.430.20.9None3NoNaNNaNParagon Semiconductor Lighting Technology Co., Ltd.NaNNaN1170.018.0NaNNaN0.953000K94.036,000NaNNaNYesNaNNaNNoNaNNaN08/31/201804/22/2019United States, CanadaES_1040003_MAD7912*_04232019020753_5273823Yes
32323027Fanimation Inc.FanimationODYN 84FPD8159*** (* = A ~ Z, 0 ~ 9 or blank)NaNOutdoor Ceiling FanStandard Fan with Light Kit84258.23.442.71.1None3NoNaNNaNSemiconductor Lighting Technology Co., Ltd.NaNNaN1200.018.0NaNNaN0.983000K92.036,000NaNNaNYesNaNNaNNoNaNNaN06/15/201807/18/2018United StatesES_1040003_FPD8159*** (* = A ~ Z, 0 ~ 9 or blank)_07192018020647_6007160No
42340903Fanimation Inc.FanimationODYN 84FPD8159* (*=variables, each variable may be A ~ Z, 0 ~ 9 or blank)NaNOutdoor Ceiling FanStandard Fan with Light Kit84382.03.834.60.9None3NoNaNNaNParagon Semiconductor Lighting Technology Co., Ltd.NaNNaN1200.018.0NaNNaN0.953000K94.036,000NaNNaNYesNaNNaNNoNaNNaN06/15/201807/08/2019United StatesES_1040003_FPD8159*_07082019051857_3137077Yes
52340900Fanimation Inc.FanimationODYN CUSTOMMAD8152*NaNOutdoor Ceiling FanStandard Fan with Light Kit72304.02.939.61.0None3NoNaNNaNParagon Semiconductor Lighting Technology Co., Ltd.NaNNaN1200.018.0NaNNaN0.953000K94.036,000NaNNaNYesNaNNaNNoNaNNaN06/14/201807/04/2019United StatesES_1040003_MAD8152*_07082019013716_9836069Yes
62335576Fanimation Inc.FanimationODYN CUSTOMMAD8152*_56 inNaNOutdoor Ceiling FanStandard Fan with Light Kit56198.02.241.81.0None3NoNaNNaNSemiconductor Lighting Technology Co., Ltd.NaNNaN1200.018.0NaNNaN0.983000K92.036,000NaNNaNYesNaNNaNNoNaNNaN06/15/201803/28/2019United StatesES_1040003_MAD8152*(* = A-Z 0-9 or blank)_56 in_03282019093037_5437444Yes
72335577Fanimation Inc.FanimationODYN CUSTOMMAD8152*_64 inNaNOutdoor Ceiling FanStandard Fan with Light Kit64282.02.533.21.2None3NoNaNNaNSemiconductor Lighting Technology Co., Ltd.NaNNaN1200.018.0NaNNaN0.983000K92.036,000NaNNaNYesNaNNaNNoNaNNaN06/15/201803/29/2019United StatesES_1040003_MAD8152*(* = A-Z 0-9 or blank)_64 in_03292019044819_4899333Yes
82340901Fanimation Inc.FanimationSTELLAR CUSTOMMAD7997*NaNOutdoor Ceiling FanStandard Fan with Light Kit72312.03.137.01.0None3NoNaNNaNParagon Semiconductor Lighting Technology Co., Ltd.NaNNaN1240.018.0NaNNaN0.953000K94.036,000NaNNaNYesNaNNaNNoNaNNaN06/14/201807/07/2019United StatesES_1040003_MAD7997*_07082019024903_4143717Yes
92340902Fanimation Inc.FanimationSTELLAR CUSTOMMAD7997*NaNOutdoor Ceiling FanStandard Fan with Light Kit84378.03.733.21.0None3NoNaNNaNParagon Semiconductor Lighting Technology Co., Ltd.NaNNaN1240.018.0NaNNaN0.953000K94.036,000NaNNaNYesNaNNaNNoNaNNaN06/14/201807/07/2019United StatesES_1040003_MAD7997*_07082019052826_3706108Yes

Last rows

ENERGY STAR Unique IDENERGY STAR PartnerBrand NameModel NameModel NumberAdditional Model InformationIndoor/OutdoorProduct TypeBlade Span (Diameter) (in.)Ceiling Fan Efficiency (CFM/W)Fan Power Consumption-Low Speed (W)Fan Power Consumption-High Speed (W)Fan Power Consumption-Standby (W)Ceiling Fan FeaturesCeiling Fan Components Warranty (Years)Shipped with ENERGY STAR Lamp(s)ENERGY STAR Lamp ESUIDAlternate ENERGY STAR Lamps ESUIDsENERGY STAR Lamp PartnerLamp Model NumberLight Source TechnologyTotal Light Output (lumens)Total Lighting Input Power (Watts)Lighting Efficiency – Measured outside the Fixture (lm/W)Lighting Efficiency – Measured at the Source (lm/W)Power Factor of Light KitLight Color Appearance (CCT)Light Color Quality (CRI)Light Source Rated Life (Hours)Light Sources Per Light KitLight Source Connection/Base TypeLight Kit DimmabilitySpecial Lighting Features (Dimming, Motion Sensing, etc.)Ceiling Fan Light Kit Warranty (yrs)Connected FunctionalityConnects UsingNotesDate Available on MarketDate CertifiedMarketsCB Model IdentifierMeets ENERGY STAR Most Efficient 2019 Criteria
2112359774WAC LightingWAC LightingMochaF-001,,F-001-* ("*" can be any length of characters or blank)Indoor Ceiling FanStandard Fan Only54207.06.436.41.4None3NoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNYesNaNNaNNoNaNNaN02/01/202005/18/2020United StatesES_22491_F-001_05182020062859_3339334Yes
2122359771WAC LightingWAC LightingMochaF-001L,,F-001L-* ("*" can be any length of characters or blank)Indoor Ceiling FanStandard Fan with Light Kit54207.06.436.41.4None3NoNaNNaNSeoul Demiconductor Co., LtdNaNNaN1440.020.0NaNNaN0.903000K93.050,000NaNNaNYesNaNNaNNoNaNNaN02/01/202005/18/2020United StatesES_22491_F-001L_05182020030358_1038151Yes
2132360008WAC LightingWAC LightingOdyssey 52F-005L,,F-005L-** ("**'' can be any length of characters or blank)Indoor Ceiling FanStandard Fan with Light Kit52155.13.628.61.4None3NoNaNNaNWAC Lighting CoNaNNaN2200.025.0NaNNaN0.902700K93.054,000NaNNaNYesNaNNaNNoNaNNaN06/15/202005/20/2020United States, CanadaES_22491_F-005L_05202020062819_6099718No
2142360009WAC LightingWAC LightingOdyssey 52F-005L,,F-005L-** ("**'' can be any length of characters or blank)Indoor Ceiling FanStandard Fan with Light Kit52155.13.628.61.4None3NoNaNNaNWAC Lighting CoNaNNaN2200.025.0NaNNaN0.903000K93.054,000NaNNaNYesNaNNaNNoNaNNaN06/15/202005/20/2020United States, CanadaES_22491_F-005L_05202020062846_6126038No
2152360010WAC LightingWAC LightingOdyssey 52F-005L,,F-005L-** ("**'' can be any length of characters or blank)Indoor Ceiling FanStandard Fan with Light Kit52155.13.628.61.4None3NoNaNNaNWAC Lighting CoNaNNaN2200.025.0NaNNaN0.903500K93.054,000NaNNaNYesNaNNaNNoNaNNaN06/15/202005/20/2020United States, CanadaES_22491_F-005L_05202020062901_6141756No
2162360011WAC LightingWAC LightingOdyssey 52F-005L,,F-005L-** ("**'' can be any length of characters or blank)Indoor Ceiling FanStandard Fan with Light Kit52155.13.628.61.4None3NoNaNNaNWAC Lighting CoNaNNaN2200.025.0NaNNaN0.904000/4100K93.054,000NaNNaNYesNaNNaNNoNaNNaN06/15/202005/20/2020United States, CanadaES_22491_F-005L_05202020062918_6158396No
2172359805WAC LightingWAC LightingORBF-004ORB,F-004-* ("*" can be any length of characters or blank),Indoor Ceiling FanStandard Fan Only44175.03.326.91.6None3NoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNYesNaNNaNNoNaNNaN01/31/202005/17/2020United StatesES_22491_F-004_05182020032937_2577395Yes
2182359775WAC LightingWAC LightingORBF-004LORB,F-004L-* ("*" can be any length of characters or blank),"*" can be any length of characters or blankIndoor Ceiling FanStandard Fan with Light Kit44175.03.326.91.6None3NoNaNNaNSeoul Demiconductor Co., LtdNaNNaN1440.020.0NaNNaN0.903000K93.050,000NaNNaNYesNaNNaNNoNaNNaN01/31/202005/17/2020United StatesES_22491_F-004L_05182020064223_4143062Yes
2192354310WAC LightingWAC Lighting Co.52 Clean52WAM52 Clean,F-003,Outdoor Ceiling FanStandard Fan with Light Kit52188.04.029.91.4None3NoNaNNaNSeoul Semiconductor Co., LtdNaNNaN1000.015.0NaNNaN0.873000K93.054,000NaNNaNYesNaNNaNNoNaNNaN03/01/202002/03/2020United States, CanadaES_22491_52WAM_02032020091728_1448190Yes
2202349604Westinghouse Lighting CorporationWestinghouse7222872228NaNIndoor Ceiling FanStandard Fan with Light Kit52160.13.532.40.9NaN3Yes2339447.0NaNWestinghouse Lighting Corporation51331LED800.09.0NaNNaN0.703000K83.0250002.0E26YesNaNNaNNoNaNNaN10/28/201911/07/2019United States, CanadaES_1018392_72228_11052019172013_2983514Yes